Identification of hub genes specific to pulmonary metastasis in osteosarcoma through integrated bioinformatics analysis

2021 ◽  
pp. 1-11
Author(s):  
Yinan Chai ◽  
Lihan Xu ◽  
Rui He ◽  
Liangjun Zhong ◽  
Yuying Wang
Keyword(s):  
Pulmonary Metastasis ◽  
Kegg Pathway ◽  
Expression Profiles ◽  
Experimental Studies ◽  
Genetic Alterations ◽  
Mapk Signaling ◽  
Receptor Interaction ◽  
Hub Genes ◽  
Pathway Analyses ◽  
Geo Database

BACKGROUND: Pulmonary metastasis is the most frequent cause of death in osteosarcoma (OS) patients. Recently, several bioinformatics studies specific to pulmonary metastatic osteosarcoma (PMOS) have been applied to identify genetic alterations. However, the interpretation and reliability of the results obtained were limited for the independent database analysis. OBJECTIVE: The expression profiles and key pathways specific to PMOS remain to be comprehensively explored. Therefore, in our study, three original datasets of GEO database were selected. METHODS: Initially, three microarray datasets (GSE14359, GSE14827, and GSE85537) were downloaded from the GEO database. Differentially expressed genes (DEGs) between PMOS and nonmetastatic osteosarcoma (NMOS) were identified and mined using DAVID. Subsequently, GO and KEGG pathway analyses were carried out for DEGs. Corresponding PPI network of DEGs was constructed based on the data collected from STRING datasets. The network was visualized with Cytoscape software, and ten hub genes were selected from the network. Finally, survival analysis of these hub genes also used the TARGET database. RESULTS: In total, 569 upregulated and 1238 downregulated genes were filtered as DEGs between PMOS and NMOS. Based on the GO analysis result, these DEGs were significantly enriched in the anatomical structure development, extracellular matrix, biological adhesion, and cell adhesion terms. Based on the KEGG pathway analysis result, these DEGs were mainly enriched in the pathways in cancer, PI3K-Akt signaling, MAPK signaling, focal adhesion, cytokine-cytokine receptor interaction, and IL-17 signaling. Hub genes (ANXA1 and CXCL12) were significantly associated with overall survival time in OS patient. CONCLUSION: Our results may provide new insight into pulmonary metastasis of OS. However, experimental studies remain necessary to elucidate the biological function and mechanism underlying PMOS.

scholarly journals High-Throughput In Vitro Gene Expression Profile to Screen of Natural Herbals for Breast Cancer Treatment

2021 ◽  
Vol 11 ◽  
Author(s):  
Ling Kui ◽  
Qinghua Kong ◽  
Xiaonan Yang ◽  
Yunbing Pan ◽  
Zetan Xu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Therapy ◽  
High Throughput ◽  
Kegg Pathway ◽  
Mapk Signaling ◽  
Diagnostic Tools ◽  
Hub Genes ◽  
Breast Cancer Therapy ◽  
Group 3 ◽  
Pathway Analyses

Breast cancer has surpassed lung cancer as the most commonly diagnosed cancer in women worldwide. Some therapeutic drugs and approaches could cause side effects and weaken the immune system. The combination of conventional therapies and traditional Chinese medicine (TCM) significantly improves treatment efficacy in breast cancer. However, the chemical composition and underlying anti-tumor mechanisms of TCM still need to be investigated. The primary aim of this study is to provide unique insights to screen the natural components for breast cancer therapy using high-throughput transcriptome analysis. Differentially expressed genes were identified based on two conditions: single samples and groups were classified according to their pharmaceutical effect. Subsequently, the sample treated with E. cochinchinensis Lour. generated the most significant DEGs set, including 1,459 DEGs, 805 upregulated and 654 downregulated. Similarly, group 3 treatment contained the most DEGs (414 DEGs, 311 upregulated and 103 downregulated). KEGG pathway analyses showed five significant pathways associated with the inflammatory and metastasis processes in cancer, which include the TNF, IL−17, NF-kappa B, MAPK signaling pathways, and transcriptional misregulation in cancer. Samples were classified into 13 groups based on their pharmaceutical effects. The results of the KEGG pathway analyses remained consistent with signal samples; group 3 presents a high significance. A total of 21 genes were significantly regulated in these five pathways, interestingly, IL6, TNFAIP3, and BRIC3 were enriched on at least two pathways, seven genes (FOSL1, S100A9, CXCL12, ID2, PRS6KA3, AREG, and DUSP6) have been reported as the target biomarkers and even the diagnostic tools in cancer therapy. In addition, weighted correlation network analysis (WGCNA) was used to identify 18 modules. Among them, blue and thistle2 were the most relevant modules. A total of 26 hub genes in blue and thistle2 modules were identified as the hub genes. In conclusion, we screened out three new TCM (R. communis L., E. cochinchinensis Lour., and B. fruticosa) that have the potential to develop natural drugs for breast cancer therapy, and obtained the therapeutic targets.

scholarly journals Database Mining of Genes of Prognostic Value for the Prostate Adenocarcinoma Microenvironment Using the Cancer Gene Atlas

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Xin Zhao ◽  
Daixing Hu ◽  
Jia Li ◽  
Guozhi Zhao ◽  
Wei Tang ◽  
...  
Keyword(s):  
Overall Survival ◽  
Immune Cell ◽  
Kegg Pathway ◽  
Clinical Sample ◽  
Expression Profiles ◽  
Prostate Adenocarcinoma ◽  
Cancer Gene ◽  
Hub Genes ◽  
Ppi Networks ◽  
Pathway Analyses

Background. Prostate adenocarcinoma (PRAD) is a common malignant tumor in elderly men. Our research uses The Cancer Gene Atlas (TCGA) database to find potential related genes for predicting the prognosis of patients with PRAD. Methods. We downloaded gene expression profiles and clinical sample information from TCGA for 490 patients with PRAD (patient age: 41-78 years). We calculated stromal and immune scores using the ESTIMATE algorithm to predict the level of stromal and immune cell infiltration. We categorized patients with PRAD in TCGA into high and low score arrays according to their median immune/stromal scores and identified differentially expressed genes (DEGs) that were significantly correlated with the prognosis of PRAD. Then, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed. The association between DEGs and overall survival was investigated by weighted Kaplan–Meier survival analysis and multivariate analysis. Furthermore, the protein-protein interaction network (PPI) of DEGs was constructed using the STRING tool. Finally, the hub genes were identified by analyzing the degree of association of PPI networks. Results. We found that 8 individual DEGs, C6, S100A12, MLC1, PAX5, C7, FAM162B, CAMK1G, and TCEAL5, were significantly predictive of favorable overall survival and one DEG, EPYC, was associated with poor overall survival. GO and KEGG pathway analyses revealed that the DEGs were associated with immune responses. Moreover, 30 hub genes were obtained using the PPI network of DEGs: ITGAM, CD4, CD3E, IL-10, LCP2, ITGB2, ZAP-70, C3, CCL19, CXCL13, CXCL9, BTK, CCL21, CD247, CD28, CD3D, FCER1G, PTPRC, TYROBP, CCR5, ITK, CCL13, CCR1, CCR2, CD79B, CYBB, IL2RG, JAK3, PLCG2, and CD19. These prominent nodes had the most associations with other genes, indicating that they might play crucial roles in the prognosis of PRAD. Conclusions. We extracted a list of genes associated with the prostate adenocarcinoma microenvironment, which might contribute to the prediction and interpretation of PRAD prognosis.

scholarly journals MAPK10 Expression as a Prognostic Marker of the Immunosuppressive Tumor Microenvironment in Human Hepatocellular Carcinoma

2021 ◽  
Vol 11 ◽  
Author(s):  
Huahui Li ◽  
Yuting Li ◽  
Ying Zhang ◽  
Binbin Tan ◽  
Tuxiong Huang ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Tumor Microenvironment ◽  
Transmembrane Protein ◽  
Cell Receptor ◽  
Receptor Activation ◽  
Mapk Signaling ◽  
Receptor Interaction ◽  
Hub Genes ◽  
Protein Protein Interaction ◽  
Pathway Analyses

Hepatocellular carcinoma (HCC) remains a devastating malignancy worldwide due to lack of effective therapy. The immune-rich contexture of HCC tumor microenvironment (TME) makes this tumor an appealing target for immune-based therapies; however, the immunosuppressive TME is still a major challenge for more efficient immunotherapy in HCC. Using bioinformatics analysis based on the TCGA database, here we found that MAPK10 is frequently down-regulated in HCC tumors and significantly correlates with poor survival of HCC patients. HCC patients with low MAPK10 expression have lower expression scores of tumor infiltration lymphocytes (TILs) and stromal cells in the TME and increased scores of tumor cells than those with high MAPK10 expression. Further transcriptomic analyses revealed that the immune activity in the TME of HCC was markedly reduced in the low-MAPK10 group of HCC patients compared to the high-MAPK10 group. Additionally, we identified 495 differentially expressed immune-associated genes (DIGs), with 482 genes down-regulated and 13 genes up-regulated in parallel with the decrease of MAPK10 expression. GO enrichment and KEGG pathway analyses indicated that the biological functions of these DIGs included cell chemotaxis, leukocyte migration and positive regulation of the response to cytokine–cytokine receptor interaction, T cell receptor activation and MAPK signaling pathway. Protein–protein interaction (PPI) analyses of the 495 DIGs revealed five potential downstream hub genes of MAPK10, including SYK, CBL, VAV1, LCK, and CD3G. Several hub genes such as SYK, LCK, and VAV1 could respond to the immunological costimulatory signaling mediated by the transmembrane protein ICAM1, which was identified as a down-regulated DIG associated with low-MAPK10 expression. Moreover, ectopic overexpression or knock-down of MAPK10 could up-regulate or down-regulate ICAM1 expression via phosphorylation of c-jun at Ser63 in HCC cell lines, respectively. Collectively, our results demonstrated that MAPK10 down-regulation likely contributes to the immunosuppressive TME of HCC, and this gene might serve as a potential immunotherapeutic target and a prognostic factor for HCC patients.

scholarly journals Screening and identification of MicroRNAs expressed in perirenal adipose tissue during rabbit growth

2019 ◽  
Author(s):  
Guoze Wang ◽  
Guo Guo ◽  
Xueting Tian ◽  
Shenqiang Hu ◽  
Kun Du ◽  
...  
Keyword(s):  
Adipose Tissue ◽  
Target Genes ◽  
Kegg Pathway ◽  
Expression Profiles ◽  
Mapk Signaling ◽  
Fat Deposition ◽  
Growth Stages ◽  
Perirenal Adipose Tissue ◽  
Go Enrichment ◽  
Pathway Analyses

AbstractMiRNAs regulate adipose tissue development, which are closely related to subcutaneous and intramuscular fat deposition and adipocyte differentiation. As an important economic and agricultural animal, rabbits have low adipose tissue deposition and are an ideal model to study adipose regulation. However, the miRNAs related to fat deposition during the growth and development of rabbits are poorly defined. In this study, miRNA-sequencing and bioinformatics analyses were used to profile the miRNAs in rabbit perirenal adipose tissue at 35, 85 and 120 days post-birth. Differentially expressed (DE) miRNAs between different stages were identified by DEseq in R. Target genes of DE miRNAs were predicted by TargetScan and miRanda. To explore the functions of identified miRNAs, Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed. Approximately 1.6 GB of data was obtained by miRNA-seq. A total of 987 miRNAs (780 known and 207 newly predicted) and 174 DE miRNAs were identified. The miRNAs ranged from 18nt to 26nt. GO enrichment and KEGG pathway analyses revealed that the target genes of the DE miRNAs were mainly involved in zinc ion binding, regulation of cell growth, MAPK signaling pathway, and other adipose hypertrophy-related pathways. Six DE miRNAs were randomly selected and their expression profiles were validated by q-PCR. In summary, we provide the first report of the miRNA profiles of rabbit adipose tissue during different growth stages. Our data provide a theoretical reference for subsequent studies on rabbit genetics, breeding and the regulatory mechanisms of adipose development.

scholarly journals Comprehensive Analysis of a circRNA-miRNA-mRNA Network to Reveal Potential Inflammation-Related Targets for Gastric Adenocarcinoma

2020 ◽  
Vol 2020 ◽  
pp. 1-15 ◽  
Author(s):  
YunXia Liu ◽  
YeFeng Xu ◽  
Feng Xiao ◽  
JianFeng Zhang ◽  
YiQing Wang ◽  
...  
Keyword(s):  
Regulatory Network ◽  
Gene Networks ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Genetic Alterations ◽  
Functional Enrichment ◽  
Receptor Interaction ◽  
Ppi Network ◽  
Hub Genes

Gastric cancer (GC) is the most common malignancy of the stomach. This study was aimed at elucidating the regulatory network of circRNA-miRNA-mRNA and identifying the precise inflammation-related targets in GC. The expression profiles of GSE83521, GSE78091, and GSE33651 were obtained from the GEO database. Interactions between miRNAs and circRNAs were investigated by the Circular RNA Interactome, and targets of miRNAs were predicted with miRTarBase. Then, a circRNA/miRNA/mRNA regulatory network was constructed. Also, functional enrichment analysis of selected differentially expressed genes (DEGs) was performed. The inflammation-/GC-related targets were collected in the GeneCards and GenLiP3 database, respectively. And a protein-protein interaction (PPI) network of DE mRNAs was constructed with STRING and Cytoscape to identify hub genes. The genetic alterations, neighboring gene networks, expression levels, and the poor prognosis of hub genes were investigated in cBioPortal, Oncomine, and Human Protein Atlas databases and Kaplan-Meier plotter, respectively. A total of 10 DE miRNAs and 33 DEGs were identified. The regulatory network contained 26 circRNAs, 10 miRNAs, and 1459 mRNAs. Functional enrichment analysis revealed that the selected 33 DEGs were involved in negative regulation of fat cell differentiation, response to wounding, extracellular matrix- (ECM-) receptor interaction, and regulation of cell growth pathways. THBS1, FN1, CALM1, COL4A1, CTGF, and IGFBP5 were selected as inflammation-related hub genes of GC in the PPI network. The genetic alterations in these hub genes were related to amplification and missense mutations. Furthermore, the genes RYR2, ERBB2, PI3KCA, and HELZ2 were connected to hub genes in this study. The hub gene levels in clinical specimens were markedly upregulated in GC tissues and correlated with poor overall survival (OS). Our results suggest that THBS1, FN1, CALM1, COL4A1, CTGF, and IGFBP5 were associated with the pathogenesis of gastric carcinogenesis and may serve as biomarkers and inflammation-related targets for GC.

scholarly journals Identification of Novel Hub Genes Through Expression Profiles Analysis in Adrenocortical Carcinoma

2020 ◽  
Author(s):  
Chenhe Yao ◽  
Xiaoling Zhao ◽  
Xuemeng Shang ◽  
Binghan Jia ◽  
Shuaijie Dou ◽  
...  
Keyword(s):  
Adrenocortical Carcinoma ◽  
Expression Profiling ◽  
Molecular Mechanisms ◽  
Cross Validation ◽  
Expression Profiles ◽  
Ppi Network ◽  
Hub Genes ◽  
Tumor Association ◽  
Prediction Of Prognosis ◽  
Geo Database

Abstract Background: Adrenocortical carcinoma (ACC) is a heterogeneous and rare malignant tumor associated with a poor prognosis. The molecular mechanisms of ACC remain elusive and more accurate biomarkers for the prediction of prognosis are needed.Methods: In this study, integrative profiling analyses were performed to identify novel hub genes in ACC to provide promising targets for future investigation. Three gene expression profiling datasets in the GEO database were used for the identification of overlapped differentially expressed genes (DEGs) following the criteria of adj.P.Value<0.05 and |log2 FC|>0.5 in ACC. Novel hub genes were screened out following a series of processes: the retrieval of DEGs with no known associations with ACC on Pubmed, then the cross-validation of expression values and significant associations with overall survival in the GEPIA2 and starBase databases, and finally the prediction of gene-tumor association in the GeneCards database.Results: Four novel hub genes were identified and two of them, TPX2 and RACGAP1, were positively correlated with the staging. Interestingly, co-expression analysis revealed that the association between TPX2 and RACGAP1 was the strongest and that the expression of HOXA5 was almost completely independent of that of RACGAP1 and TPX2. Furthermore, the PPI network consisting of four novel genes and seed genes in ACC revealed that HOXA5, TPX2, and RACGAP1 were all associated with TP53. Conclusions: This study identified four novel hub genes (TPX2, RACHAP1, HXOA5 and FMO2) that may play crucial roles in the tumorigenesis and the prediction of prognosis of ACC.

scholarly journals Anticancer Effects of Emodin on HepG2 Cell: Evidence from Bioinformatic Analysis

2019 ◽  
Vol 2019 ◽  
pp. 1-14 ◽  
Author(s):  
Rui-sheng Zhou ◽  
Xiong-Wen Wang ◽  
Qin-feng Sun ◽  
Zeng Jie Ye ◽  
Jian-wei Liu ◽  
...  
Keyword(s):  
Signaling Pathway ◽  
Hepg2 Cells ◽  
Molecular Mechanisms ◽  
Mapk Signaling ◽  
Ion Concentration ◽  
Receptor Interaction ◽  
Pathway Enrichment Analysis ◽  
Mrna Levels ◽  
Hub Genes ◽  
Positive Regulation

Hepatocellular carcinoma (HCC) is a primary cause of cancer-related death in the world. Despite the fact that there are many methods to treat HCC, the 5-year survival rate of HCC is still at a low level. Emodin can inhibit the growth of HCC cells invitroand invivo. However, the gene regulation of emodin in HCC has not been well studied. In our research, RNA sequencing technology was used to identify the differentially expressed genes (DEGs) in HepG2 cells induced by emodin. A total of 859 DEGs were identified, including 712 downregulated genes and 147 upregulated genes in HepG2 cells treated with emodin. We used DAVID for function and pathway enrichment analysis. The protein-protein interaction (PPI) network was constructed using STRING, and Cytoscape was used for module analysis. The enriched functions and pathways of the DEGs include positive regulation of apoptotic process, structural molecule activity and lipopolysaccharide binding, protein digestion and absorption, ECM-receptor interaction, complement and coagulation cascades, and MAPK signaling pathway. 25 hub genes were identified and pathway analysis revealed that these genes were mainly enriched in neuropeptide signaling pathway, inflammatory response, and positive regulation of cytosolic calcium ion concentration. Survival analysis showed that LPAR6, C5, SSTR5, GPR68, and P2RY4 may be involved in the molecular mechanisms of emodin therapy for HCC. A quantitative real-time PCR (qRT-PCR) assay showed that the mRNA levels of LPAR6, C5, SSTR5, GPR68, and P2RY4 were significantly decreased in HepG2 cells treated with emodin. In conclusion, the identified DEGs and hub genes in the present study provide new clues for further researches on the molecular mechanisms of emodin.

scholarly journals Electroacupuncture Alleviates Experimental Chronic Inflammatory Pain by Inhibiting Calcium Voltage-Gated Channel-Mediated Inflammation

2020 ◽  
Vol 2020 ◽  
pp. 1-10 ◽  
Author(s):  
Jie Zhou ◽  
Ying Jin ◽  
Ruijie Ma ◽  
Hongyun Song ◽  
Qin Chen ◽  
...  
Keyword(s):  
Signaling Pathway ◽  
Inflammatory Pain ◽  
Expression Profiles ◽  
Arachidonic Acid Metabolism ◽  
Receptor Interaction ◽  
Bioinformatics Analyses ◽  
Protein Coding ◽  
Chronic Inflammatory Pain ◽  
Gated Channel ◽  
Pathway Analyses

Background. Both experimental and clinical studies have shown that electroacupuncture (EA) administration ameliorates chronic inflammatory pain (CIP). However, the multifaceted mechanism underlying the effects of EA on CIP is poorly understood. In this study, the mRNA transcriptome was used to study various therapeutic targets of EA. Methods. Using RNA-sequencing, protein-coding mRNA expression profiles of the L4-L5 dorsal root ganglion (DRG) were examined in the control (CN), complete Freund’s adjuvant- (CFA-) induced CIP, and EA-treated CIP groups. A series of bioinformatics analyses was performed; “EA-reversed upregulated genes with CIP” (up-DEGs) and “EA-reversed downregulated genes with CIP” (down-DEGs) were identified. Thereafter, based on up-DEGs and down-DEGs, biological functions and signaling pathways were enriched using gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) pathway analyses. Results. In total, 189 DEGs were identified, including 134 up- and 55 down-DEGs, which were enriched in arachidonic acid metabolism (rno00590), glutamatergic synapse (rno04724), serotonergic synapse (rno04726), FoxO signaling pathway (rno04068), insulin signaling pathway (rno04910), amyotrophic lateral sclerosis (rno05014), cholinergic synapse (rno04725), ECM-receptor interaction (rno04512), and choline metabolism in cancer (rno05231). Conclusion. We identified a few GOs, pathways, and genes that could play key roles in the amelioration of CIP by EA. Hence, this study may provide a theoretical basis for CIP amelioration by EA.

scholarly journals Diagnostic biomarker candidates for pulpitis revealed by bioinformatics analysis of merged microarray gene expression datasets

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Ming Chen ◽  
Junkai Zeng ◽  
Yeqing Yang ◽  
Buling Wu
Keyword(s):  
Gene Expression ◽  
Dental Pulp ◽  
Bioinformatics Analysis ◽  
Kegg Pathway ◽  
Enrichment Analysis ◽  
Biological Pathways ◽  
Signalling Pathway ◽  
Diagnostic Biomarker ◽  
Hub Genes ◽  
Geo Database

Abstract Background Pulpitis is an inflammatory disease, the grade of which is classified according to the level of inflammation. Traditional methods of evaluating the status of dental pulp tissue in clinical practice have limitations. The rapid and accurate diagnosis of pulpitis is essential for determining the appropriate treatment. By integrating different datasets from the Gene Expression Omnibus (GEO) database, we analysed a merged expression matrix of pulpitis, aiming to identify biological pathways and diagnostic biomarkers of pulpitis. Methods By integrating two datasets (GSE77459 and GSE92681) in the GEO database using the sva and limma packages of R, differentially expressed genes (DEGs) of pulpitis were identified. Then, the DEGs were analysed to identify biological pathways of dental pulp inflammation with Gene Ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis and Gene Set Enrichment Analysis (GSEA). Protein–protein interaction (PPI) networks and modules were constructed to identify hub genes with the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and Cytoscape. Results A total of 470 DEGs comprising 394 upregulated and 76 downregulated genes were found in pulpitis tissue. GO analysis revealed that the DEGs were enriched in biological processes related to inflammation, and the enriched pathways in the KEGG pathway analysis were cytokine-cytokine receptor interaction, chemokine signalling pathway and NF-κB signalling pathway. The GSEA results provided further functional annotations, including complement system, IL6/JAK/STAT3 signalling pathway and inflammatory response pathways. According to the degrees of nodes in the PPI network, 10 hub genes were identified, and 8 diagnostic biomarker candidates were screened: PTPRC, CD86, CCL2, IL6, TLR8, MMP9, CXCL8 and ICAM1. Conclusions With bioinformatics analysis of merged datasets, biomarker candidates of pulpitis were screened and the findings may be as reference to develop a new method of pulpitis diagnosis.

scholarly journals Identification of Key Genes and Pathways Associated with Mast Cells Resting in Meningioma

2020 ◽  
Author(s):  
Hui Xie ◽  
Xiao-hui Ding ◽  
Ce Yuan ◽  
Jin-jiang Li ◽  
Zhao-yang Li ◽  
...  
Keyword(s):  
Gene Expression ◽  
Mast Cells ◽  
Signaling Pathway ◽  
Molecular Mechanisms ◽  
Immune Cell ◽  
Risk Model ◽  
Kegg Pathway ◽  
Expression Profiles ◽  
Receptor Interaction ◽  
Key Genes

Abstract Background: To identify candidate key genes and pathways related to mast cells resting in meningioma and the underlying molecular mechanisms of meningioma.Methods: Gene expression profiles of GSE43290 and GSE16581 datasets were obtained from the Gene Expression Omnibus (GEO) database. GO and KEGG pathway enrichments of DEGs were analyzed using the ClusterProfiler package in R. The protein-protein interaction network (PPI), and TF-miRNA- mRNA co-expression networks were constructed. Further, the difference in immune infiltration was investigated using the CIBERSORT algorithm.Results: A total of 1499 DEGs were identified between tumor and normal controls. The analysis of the immune cell infiltration landscape showed that the probability of distribution of memory B cells, regulatory T cells (Tregs), and resting mast cells in tumor samples were significantly higher than those in the controls. Moreover, through WGCNA analysis, the module related to mast cells resting contained 158 DEGs, and KEGG pathway analysis revealed that the DEGs were dominant in the TNF signaling pathway, cytokine-cytokine receptor interaction, and IL-17 signaling pathway. Survival analysis of hub genes related to mast cells resting showed that the risk model was constructed based on 9 key genes. The TF-miRNA- mRNA co-regulation network, including MYC-miR-145-5p, TNFAIP3-miR-29c-3p, and TNFAIP3-hsa-miR-335-3p, were obtained. Further, 36 nodes and 197 interactions in the PPI network were identified. Conclusions: The results of this study revealed candidate key genes, miRNAs, and pathways related to mast cells resting involved in meningioma development, providing potential therapeutic targets for meningioma treatment.

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